scale_bodyAdjust the size of a body by setting a uniform or per-axis scale factor, with an optional anchor point for controlled resizing.
Scale a body uniformly or non-uniformly
| Name | Required | Description | Default |
|---|---|---|---|
| scale | Yes | Uniform scale factor | |
| scale_x | No | X scale (overrides uniform scale) | |
| scale_y | No | Y scale | |
| scale_z | No | Z scale | |
| anchor_x | No | Scale anchor point X | |
| anchor_y | No | Scale anchor point Y | |
| anchor_z | No | Scale anchor point Z | |
| body_name | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate this is a mutable operation (readOnlyHint=false), non-idempotent, and non-destructive. The description adds that scaling can be uniform or non-uniform, which provides useful context beyond annotations. However, it doesn't mention important behavioral aspects like coordinate system implications, effect on constraints/parameters, or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core functionality without any wasted words. It's appropriately sized for a transformation operation with good schema documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a geometric transformation tool with 8 parameters, no output schema, and moderate annotation coverage, the description is adequate but minimal. It covers the scaling modes but lacks information about coordinate systems, effect on geometry properties, or typical use cases that would help an agent understand when and how to apply this transformation correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 88% schema description coverage, the schema already documents most parameters well. The description adds the concept of uniform vs. non-uniform scaling, which helps interpret the scale vs. scale_x/y/z parameters, but doesn't provide additional syntax, format, or interaction details beyond what's in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Scale') and resource ('a body'), specifying both uniform and non-uniform scaling modes. It distinguishes from sibling tools like 'move_body' or 'mirror' by focusing on scaling transformations, though it doesn't explicitly differentiate from similar transformation tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, when scaling is appropriate versus other transformations, or how it relates to sibling tools like 'move_body' or transformation patterns.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.